{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5f673202-c42f-4ee7-85e1-1c06ae7e7202",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import os\n",
    "import matplotlib as mpl\n",
    "from scipy.stats import lognorm\n",
    "from scipy.stats import beta \n",
    "import scipy as scp\n",
    "import matplotlib as mpl\n",
    "\n",
    "mpl.rc('font',family = 'Times New Roman')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "beaf9f91-7a87-4239-bda7-6645549829cc",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def Rsquared(x,y):\n",
    "    SStot = 0\n",
    "    for i in range(len(y)):\n",
    "        SStot=SStot+(y[i]-np.mean(y))**2\n",
    "\n",
    "    SSres = 0\n",
    "\n",
    "    for i in range(len(y)):\n",
    "        SSres=SSres+(y[i]-x[i])**2\n",
    "\n",
    "    return 1-(SSres/SStot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6a058ae2-3ea5-4854-a5f2-5b272c5153f3",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "g = 9.805\n",
    "\n",
    "H = 16.5\n",
    "R = 13.9\n",
    "n = 8\n",
    "bw = 2*np.pi*R/n\n",
    "\n",
    "fillr = 0.95\n",
    "\n",
    "ro = 0.998\n",
    "ph = ro*g*H*fillr\n",
    "p = ph*bw\n",
    "\n",
    "tb = 6/1000\n",
    "tw = 17/1000\n",
    "A = bw*tb\n",
    "I = bw*tb**3/12\n",
    "Zp = bw*tb**2/4\n",
    "Es = 210000000\n",
    "v = 0.3 \n",
    "Fys = 235000\n",
    "My = Fys*Zp\n",
    "\n",
    "ros = 7.850 #density of steel\n",
    "Ww = ros*g*H*bw*tw #weight of wall over one side of the strip\n",
    "tr = 31/1000\n",
    "mr = 35\n",
    "Wr = mr*g #weight of roof\n",
    "Wrr = Wr/n\n",
    "mtot = ro*H*fillr*np.pi*R**2\n",
    "Wtot = mtot*g\n",
    "\n",
    "kuu = Es*bw*(tw/R)**1.5/((3*(1-v**2))**0.25)\n",
    "ktt = Es*bw*tw**2*(tw/R)**0.5/(2*(3*(1-v**2))**0.75)\n",
    "ktu = -Es*bw*tw*(tw/R)/(2*(3*(1-v**2))**0.5)\n",
    "\n",
    "kuus = kuu-ktu**2/ktt\n",
    "dtu = -ktu/(ktt*kuu-ktu**2)\n",
    "dtt = kuu/(ktt*kuu-ktu**2)\n",
    "\n",
    "Ly = (6*My/p)**0.5\n",
    "wy = p*Ly**4/(72*Es*I)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bbca4ba7-f409-4296-a5a9-97bfe4c190e1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.003857565057422568"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e219adee-6f65-4307-91e2-9e3d169669ac",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#String Solution\n",
    "L = np.linspace(0,5,1000)\n",
    "N = np.zeros(len(L))\n",
    "for i in range(len(L)):\n",
    "    N[i] = 0.55*p*L[i]*((kuus/p)/(1+kuus*L[i]/(A*Es)))**(1/3)\n",
    "    \n",
    "Vs = np.zeros(len(L))\n",
    "ws = np.zeros(len(L))\n",
    "\n",
    "for i in range(len(L)):\n",
    "    Vs[i] = p*L[i]\n",
    "    if(i!=0):\n",
    "        ws[i] = p*L[i]**2/(2*N[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "170bd325-9eb9-4ebd-aa71-f80ade62832b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#Bending Solution\n",
    "wb = np.zeros(len(L))\n",
    "Vb = np.zeros(len(L))\n",
    "\n",
    "for i in range(1,len(L)):\n",
    "    M1 = -((ktt)/(ktt+2*Es*I/L[i]))*(p*L[i]**2/6)\n",
    "    if(abs(M1)>My):\n",
    "        M1 = -My\n",
    "    wb[i] = p*L[i]**4/(24*Es*I)+M1*L[i]**2/(6*Es*I)\n",
    "    Vb[i] = p*L[i]/2 - M1/L[i]\n",
    "    Lmax = 3.414*(My/p)**0.5\n",
    "    if(L[i]>=Lmax):\n",
    "        Vb[i] = p*Lmax/2 - M1/Lmax\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "971d08b4-4726-413b-8225-43b966ca97ad",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pull = np.loadtxt('./ResultsBP/disp.out')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "33d48d21-b1d6-4f77-8d6b-41c57a215c87",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1d9ddef2110>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plt.title('Strip of Base Plate of 11.83 m width')\n",
    "plt.plot((pull[:,1]),(pull[:,0]),label='Beam FE Model Bakalis et al.(2017)')\n",
    "plt.xlim(0,0.5)\n",
    "plt.ylim(0,5000)\n",
    "plt.plot(wb,Vb,label='Bending Solution Malhotra & Veletsos (1994)')\n",
    "plt.plot(ws,Vs,label='String Solution Malhotra & Veletsos (1994)')\n",
    "#plt.plot((0.006,0.006),(0,3000),ls='--',color='k')\n",
    "plt.xlabel(r'Uplift, $w$ (m)')\n",
    "plt.ylabel(r'Force, $F$ (kN)')\n",
    "#plt.plot((0,0.0049),(0,574),color='k')\n",
    "#plt.plot((0.0049,0.5),(574,3300),color='k',label='Proposed method')\n",
    "plt.legend()\n",
    "\n",
    "\n",
    "\n",
    "#plt.savefig('C:/Users/rober/Documents/ROSE/PostDoc/Figure2_P2.tiff',dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "81a00a5b-501a-4096-8150-9d2c2157d5e2",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def Rotation_Uplift(theta):\n",
    "    Lm2a=Ly+0.01\n",
    "    Lm2b=0\n",
    "    true = 0\n",
    "    while(true==0):\n",
    "        wm2 = theta/((2/Lm2a)-(1/(2*R)))\n",
    "        N2 = 0.55*(Lm2a-Ly)*p*((kuus/p)/(1+kuus*(Lm2a-Ly)/(A*Es)))**(1/3)\n",
    "        Lm2b = (2*wm2*N2/p)**0.5+Ly\n",
    "        if(abs(Lm2a-Lm2b)<0.001):\n",
    "            true = 1\n",
    "        else:\n",
    "            Lm2a=Lm2b\n",
    "    return wm2,Lm2b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a8540e4d-3d1c-48a2-8947-919fcac1942f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.89637423333081"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wpl1,Lpl1 = Rotation_Uplift(0.2)\n",
    "wpl1/wy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "788dc88f-dc54-43d8-aea4-03ea4de3f316",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "40.86437250869486"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wpl2,Lpl2 = Rotation_Uplift(0.4)\n",
    "wpl2/wy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "67cb8b5e-f57a-4252-b05b-7bdedd456ec6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "L1t =np.linspace(0.1,0.65,1000)\n",
    "w1t =np.zeros(len(L1t))\n",
    "\n",
    "for i in range(len(L1t)):\n",
    "    true = 0\n",
    "    N = 300\n",
    "    #print(L1t[i])\n",
    "\n",
    "    while(true==0):\n",
    "        lam = (N*L1t[i]**2/(Es*I))**0.5\n",
    "        dtheta = 0\n",
    "        M1 = ((p*L1t[i]/N)*(1-(2/lam)*np.tanh(lam/2))+dtu*N-dtheta)/(L1t[i]/(Es*I*lam)*np.tanh(lam/2)+dtt)\n",
    "        if(abs(M1)<My):\n",
    "            M1 = -M1\n",
    "        else:\n",
    "            M1 = -My\n",
    "\n",
    "        C = ((M1*L1t[i])/(Es*I))*(1/np.sinh(lam))+(p*L1t[i]/N)*np.tanh(lam/2)\n",
    "        D = -p*L1t[i]/N\n",
    "        u1 = (N*L1t[i]/(A*Es))-((D**2*L1t[i]/(2*lam**2))*(-0.5+((lam**2)/3)+(2*np.sinh(lam)/lam)+(np.sinh(2*lam)/(4*lam))-(2*np.cosh(lam))))-((C**2*L1t[i]/(2*lam**2))*(1.5-(2*np.sinh(lam)/lam)+(np.sinh(2*lam)/(4*lam))))-((C*D*L1t[i]/(2*lam**2))*(lam-1/(2*lam)-(2*np.sinh(lam))+(np.cosh(2*lam)/(2*lam))))\n",
    "\n",
    "        N1 = -(kuu-(ktu**2/ktt))*u1+(ktu/ktt)*M1\n",
    "        #print(N1)\n",
    "        if(abs(N-N1)<0.1):\n",
    "            true = 1\n",
    "        else:\n",
    "            N = N1\n",
    "        #print(N)\n",
    "    #print(i)\n",
    "    w1t[i] = (M1/N)*(1-(lam/np.sinh(lam)))+(p*L1t[i]**2/(2*N))*(1-(2/lam)*np.tanh(lam/2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "93d181ea-e20b-4dc6-8f20-01ebfbbf9d4d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "winkSpring = np.loadtxt('./ResultsBP/WinklerSprings.out')\n",
    "lb = 50/1000\n",
    "\n",
    "nZeros = np.zeros(len(winkSpring))\n",
    "Lfe = np.zeros(len(winkSpring))\n",
    "\n",
    "for i in range(len(Lfe)):\n",
    "    if(winkSpring[i][-1]==0):\n",
    "        for j in range(len(winkSpring[i])):\n",
    "            if(winkSpring[i][j] == 0):\n",
    "                nZeros[i] = nZeros[i]+1\n",
    "            \n",
    "Lfe = nZeros*lb  \n",
    "ind = []\n",
    "ind.append(0)\n",
    "for i in range(len(Lfe)-1):\n",
    "    if(Lfe[i]!=Lfe[i+1]):\n",
    "        ind.append(i+1)\n",
    "        \n",
    "for i in range(1,len(ind)):\n",
    "    delta = (Lfe[ind[i]]-Lfe[ind[i-1]])/(ind[i]-ind[i-1])\n",
    "    for j in range(ind[i-1],ind[i]):\n",
    "        Lfe[j] = Lfe[ind[i-1]] + delta*(j-ind[i-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "88a78515-5d80-419a-804f-d4313272b3d2",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def Uplift_SepL(w):\n",
    "    if(w<=wy):\n",
    "        return w*(Ly/wy)\n",
    "    else:\n",
    "        Lm2a=Ly+0.01\n",
    "        Lm2b=0\n",
    "        true = 0\n",
    "        while(true==0):\n",
    "            N2 = 0.55*(Lm2a-Ly)*p*((kuus/p)/(1+kuus*(Lm2a-Ly)/(A*Es)))**(1/3)\n",
    "            Lm2b = (2*w*N2/p)**0.5+Ly\n",
    "            if(abs(Lm2a-Lm2b)<0.0001):\n",
    "                true = 1\n",
    "            else:\n",
    "                Lm2a=Lm2b\n",
    "            #print(Lm2a)\n",
    "        return Lm2b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "417e298a-b609-47e3-b53d-70a61202c9b9",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "w2 = np.linspace(0,0.5,100)\n",
    "L2 = np.zeros(len(w2))\n",
    "for i in range(len(w2)):\n",
    "    L2[i] = Uplift_SepL(w2[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "aa40cb5f-d04a-494d-b8fc-918502282482",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "w3 = w1t\n",
    "L3 = np.zeros(len(w3))\n",
    "for i in range(len(w3)):\n",
    "    L3[i] = Uplift_SepL(w3[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c789244c-6f01-4d3f-88b9-0edf0f39d34f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8257047828813712"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Rsquared(L3,L1t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c4bb172b-b5d7-4936-ad8f-9f463a2b5f6b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.050778358000687134"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "REL = np.zeros((len(L1t)))\n",
    "\n",
    "for i in range(len(L1t)):\n",
    "    REL[i] = abs(L1t[i]-L3[i])\n",
    "MREL= np.mean(REL)\n",
    "MREL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "54b299e4-56de-4bd6-9fb7-6c0716046ad6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#dataBKL = np.loadtxt('C:/Users/rober/Documents/ROSE/PostDoc/Tanks/DDBDTanks/DataBK_L_1.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "7708b543-1d77-47e4-90b2-af14816d567e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Separation Length, $L$ [m]')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plt.plot(wb,L)\n",
    "#plt.plot(ws,L)\n",
    "w1 = np.linspace(0,1.5,1000)\n",
    "L1 = np.zeros(len(w1))\n",
    "for i in range(len(w1)):\n",
    "    L1[i] = 2*w1[i]/(0.2+w1[i]/(2*R))\n",
    "\n",
    "plt.plot(w1,L1)\n",
    "plt.plot(pull[:,1],Lfe,label='Finite Elements Solution')\n",
    "plt.plot(w1t,L1t,label='Exact Solution')\n",
    "plt.plot(w2,L2,color='k',label='Proposed Solution')\n",
    "#plt.plot(dataBKL[:,0]/1000,dataBKL[:,1]/1000,label='Refined FE, B&K')\n",
    "#plt.plot(ws,ws/(0.2+ws/(2*R)))\n",
    "plt.xlim(0,0.2)\n",
    "plt.ylim(0,2)\n",
    "\n",
    "plt.legend()\n",
    "plt.xlabel(r'Uplift, $w$ [m]')\n",
    "plt.ylabel(r'Separation Length, $L$ [m]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ab2420b0-8805-4deb-8b70-f396faa23b8d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1d9e0533ad0>]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(wb,Vb)\n",
    "plt.plot(ws,Vs)\n",
    "plt.xlim(0,0.3)\n",
    "plt.ylim(0,3000)\n",
    "plt.plot((0.005,0.005),(0,3000),ls='--',color='k')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "5c3ab52f-d600-4e48-9462-721d73c0231b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model Built\n",
      "Pushover analysis completed\n",
      "Done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING analysis Static - no Integrator specified, \n",
      " StaticIntegrator default will be used\n"
     ]
    }
   ],
   "source": [
    "#Units in m and kN\n",
    "import openseespy.opensees as op\n",
    "op.wipe()\n",
    "op.model('basic', '-ndm', 2, '-ndf', 3) \n",
    "\n",
    "op.node(1, 0.0, 0.0)\n",
    "op.node(2, 0.0, 0.0)\n",
    "\n",
    "op.fix(1, 1, 1, 1)\n",
    "nodeR = 1\n",
    "nodeC = 2\n",
    "op.equalDOF(nodeR, nodeC, 2, 3)\n",
    "\n",
    "matTag1 = 5\n",
    "ePf1 = 350\n",
    "ePd1 = 0.0038\n",
    "k1 = ePf1/ePd1\n",
    "\n",
    "ePf2 = 550\n",
    "ePd2 = 0.09\n",
    "k2 = (ePf2-ePf1)/(ePd2-ePd1)\n",
    "\n",
    "sigAct = ePf1\n",
    "beta =0.38\n",
    "epsSlip = 0.0\n",
    "epsBear = 0.2\n",
    "\n",
    "ePf3 = 1800\n",
    "ePd3 = 0.4\n",
    "\n",
    "k3 = (ePf3-ePf2)/(ePd3-ePd2)\n",
    "\n",
    "rBear = k3/k1\n",
    "\n",
    "op.uniaxialMaterial('SelfCentering',matTag1,k1,k2,sigAct,beta,epsSlip,epsBear,rBear)\n",
    "matTag2 = 6\n",
    "K = 800/0.3\n",
    "op.uniaxialMaterial('Elastic',matTag2,K,0,1e10)\n",
    "\n",
    "#matTag3 = 7\n",
    "#k2 = ePf2/ePd2\n",
    "#dy = ePd1\n",
    "#Fy = k2*dy\n",
    "#b = 0\n",
    "\n",
    "#op.uniaxialMaterial('Steel01',matTag3,Fy,k2,b)\n",
    "\n",
    "ParMatTag = 8\n",
    "op.uniaxialMaterial('Parallel',ParMatTag,matTag1,matTag2)\n",
    "\n",
    "\n",
    "eleID = 5\n",
    "\n",
    "op.element('zeroLength', eleID, nodeR, nodeC, '-mat', ParMatTag, '-dir',1)\n",
    "\n",
    "print(\"Model Built\")\n",
    "\n",
    "op.recorder('Node', '-file', 'Force.out','-node', 1, '-dof', 1, 'reaction')\n",
    "op.recorder('Node', '-file', 'DispS.out','-node', 2, '-dof', 1, 'disp')\n",
    "\n",
    "displist = [3/1000,0,3/1000,0,10/1000,0,10/1000,0,20/1000,0,20/1000,0,30/1000,0,30/1000,0,50/1000,0,50/1000,0,100/1000,0,100/1000,0,150/1000,0,150/1000,0,200/1000,0,200/1000,0,300/1000,0,300/1000,0,500/1000,0,500/1000,1000/1000,0,1000/1000,0]\n",
    "#displist = [50/1000,0,50/1000,0]\n",
    "dstep = 1/1000\n",
    "ctrlNode = 2 # node where disp is read for disp control\n",
    "dof  = 1 # degree of freedom read for disp control (1 = x displacement)\n",
    "\n",
    "POtag = 100;\n",
    "linTS = 2\n",
    "op.timeSeries('Linear',linTS)\n",
    "\n",
    "op.pattern('Plain', POtag, linTS)     \n",
    "op.load(ctrlNode,1,0,0)\n",
    "op.reactions()\n",
    "Disp = [op.nodeDisp(ctrlNode,dof)]\n",
    "force = [op.nodeReaction(1,dof)]\n",
    "\n",
    "testParams = [1.e-4, 50]\n",
    "\n",
    "op.numberer('RCM') # renumber dof's to minimize band-width (optimization), if you want to\n",
    "op.system('BandGeneral') # how to store and solve the system of equations in the analysis\n",
    "op.constraints('Plain') # how it handles boundary conditions\n",
    "op.test('NormDispIncr',*testParams) # determine if convergence has been achieved at the end of an iteration step\n",
    "op.algorithm('Newton') # use Newton's solution algorithm: updates tangent stiffness at every iteration\n",
    "op.analysis('Static') # define type of analysis static or transient\n",
    "\n",
    "ok = 0\n",
    "for j in range(0,len(displist)):\n",
    "    if(ok != 0):\n",
    "        break\n",
    "    dispnew = displist[j]\n",
    "    if(j > 0):\n",
    "        dispold = displist[j-1]\n",
    "    else:\n",
    "        dispold = 0\n",
    "    disp = dispnew - dispold\n",
    "    if(disp > 0):\n",
    "        dsteps = dstep\n",
    "    else:\n",
    "        dsteps = -dstep\n",
    "    nstep = int(disp/dsteps)\n",
    "    op.integrator('DisplacementControl', ctrlNode, dof, dsteps) # determine the next time step for an analysis\n",
    "    for i in range(nstep):\n",
    "        ok = op.analyze(1)\n",
    "        if(ok != 0):\n",
    "            testParams2 = [1.e-4, 2000]\n",
    "            op.test('EnergyIncr',*testParams2)\n",
    "            op.algorithm('Newton','-initial')\n",
    "            print(\"Trying Newton with Initial Tangent ..\")\n",
    "            ok = op.analyze(1)\n",
    "            op.test('NormDispIncr',*testParams) \n",
    "            op.algorithm('Newton') \n",
    "        if(ok!= 0):\n",
    "            op.algorithm('Broyden',50)\n",
    "            op.test('RelativeNormDispIncr',*testParams2)\n",
    "            print(\"Trying Broyden ..\")\n",
    "            ok = op.analyze(1) \n",
    "            op.test('NormDispIncr',*testParams) \n",
    "            op.algorithm('Newton') \n",
    "        if(ok != 0):\n",
    "            op.algorithm('NewtonLineSearch')\n",
    "            print(\"Trying NewtonWithLineSearch ..\")\n",
    "            ok = op.analyze(1)\n",
    "            op.algorithm('Newton') # use Newton's solution algorithm: updates tangent stiffness at every iteration\n",
    "        if(ok == 0):\n",
    "            #ctrlDisp.append(op.nodeDisp(ctrlNode,dof))\n",
    "            #force.append(op.nodeReaction(1,dof))\n",
    "            dsp = round(op.nodeDisp(ctrlNode,dof),3)\n",
    "            #print(f'Displacement {dsp} reached of {dispnew}')\n",
    "        else:\n",
    "            break\n",
    "print('Pushover analysis completed')\n",
    "\n",
    "if(ok != 0):\n",
    "    print('Problem with Pushover')\n",
    "else:\n",
    "    print('Done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "df747cab-a5d6-4885-843c-e25787f644cf",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "f = np.loadtxt('Force.out')\n",
    "d = np.loadtxt('DispS.out')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "db4ca0ad-455a-4f07-9873-db07d6145c6e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8452"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "id": "f58809fa-ef76-4542-adde-257f112cb2c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "pullC = np.loadtxt('./ResultsBP/disp_Cyclic.out')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "1fdc9066-77d5-426d-a02e-64f23da8a124",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.title('Half Cycle Pushover')\n",
    "plt.plot((pullC[:,1]),(pullC[:,0]),label='Bakalis et al. (2017)')\n",
    "plt.plot(d,-f,label='Calibrated Self-Centering uniaxial zero length spring')\n",
    "#plt.plot((dy,dy),(0,2000),color='k',ls='--')\n",
    "#plt.plot((dc,dc),(0,2000),color='k',ls='--')\n",
    "#plt.plot((0,0.3),(Fc,Fc),color='k',ls='--')\n",
    "plt.ylim(-50,3000)\n",
    "plt.xlim(0,0.4)\n",
    "plt.xlabel(r'Uplift, $w$ (m)')\n",
    "plt.ylabel(r'Force, $F$ (kN)')\n",
    "plt.legend()\n",
    "plt.savefig('C:/Users/rober/Documents/ROSE/PostDoc/Figure3_P2.tiff',dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "6084e076-c410-4fe6-b55f-bb532043f32b",
   "metadata": {},
   "outputs": [],
   "source": [
    "inx = []\n",
    "for i in range(0,len(pullC[:,1])-1):\n",
    "    if(i == 0):\n",
    "        inx.append(1)\n",
    "    if(pullC[i-1,1]>pullC[i,1] and pullC[i+1,1]>pullC[i,1]):\n",
    "        inx.append(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "31ce15d9-e6b6-4172-9b2c-5c099c849876",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "inxN = []\n",
    "for i in range(0,len(d)-1):\n",
    "    if(i == 0):\n",
    "        inxN.append(1)\n",
    "    if(d[i-1]>d[i] and d[i+1]>d[i]):\n",
    "        inxN.append(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "a222c9fc-b4ca-45ef-875a-78a6f1a6a85e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "21"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(inxN)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "4bfa9804-0c0a-42e6-b5bd-77fa89c125e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1d9e14b2b90>]"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n =18\n",
    "plt.plot(pullC[inx[n]:inx[n+1],1],pullC[inx[n]:inx[n+1],0])\n",
    "plt.plot(d[inxN[n]:inxN[n+1]],-f[inxN[n]:inxN[n+1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "8bc1d105-9a43-4506-a399-a7f6d6089fad",
   "metadata": {},
   "outputs": [],
   "source": [
    "E = np.zeros(len(inx))\n",
    "ksi = np.zeros(len(inx))\n",
    "dmax = np.zeros(len(inx))\n",
    "\n",
    "for i in range(1,len(inx)):\n",
    "    E[i] = 0.0\n",
    "    for j in range(inx[i-1],inx[i]):\n",
    "        E[i] = E[i] + 2*0.5*(pullC[j-1,0]+pullC[j,0])*(pullC[j,1]-pullC[j-1,1])\n",
    "    ksi[i] = E[i]/(2*np.pi*max(pullC[inx[i-1]:inx[i],0])*max(pullC[inx[i-1]:inx[i],1]))\n",
    "    dmax[i] = max(pullC[inx[i-1]:inx[i],1])\n",
    "    \n",
    "Eabs = np.zeros(len(E))\n",
    "\n",
    "for i in range(1,len(Eabs)):\n",
    "    Eabs[i] = Eabs[i-1]+E[i] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "cd497325-17df-4730-901e-96cd8a5a3d3f",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "EN = np.zeros(len(inxN))\n",
    "ksiN = np.zeros(len(inxN))\n",
    "dmaxN = np.zeros(len(inxN))\n",
    "\n",
    "for i in range(1,len(inxN)):\n",
    "    EN[i] = 0.0\n",
    "    for j in range(inxN[i-1],inxN[i]):\n",
    "        EN[i] = EN[i] + 2*0.5*(-f[j-1]-f[j])*(d[j]-d[j-1])\n",
    "    ksiN[i] = EN[i]/(2*np.pi*max(-f[inxN[i-1]:inxN[i]])*max(d[inxN[i-1]:inxN[i]]))\n",
    "    dmaxN[i] = max(d[inxN[i-1]:inxN[i]])\n",
    "    \n",
    "EabsN = np.zeros(len(EN))\n",
    "\n",
    "for i in range(1,len(EabsN)):\n",
    "    EabsN[i] = EabsN[i-1]+EN[i] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "a67df84f-72bb-46b9-af8f-e6560ed1f6e7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.08267850069856747"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RE = np.zeros((len(Eabs[10:20])))\n",
    "\n",
    "for i in range(10,len(Eabs)-1):\n",
    "    RE[i-10] = abs(Eabs[i]-EabsN[i])/Eabs[i]\n",
    "   \n",
    "MRE = np.mean(RE)\n",
    "MRE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "4738695a-a451-4b2c-9bc3-b4f4f90cc80a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9732489328500151"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Rsquared(EabsN[10:20],Eabs[10:20])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "5a16e17b-3184-421f-b4ff-4e95bc52b3d7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1725345927476473"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "REk = np.zeros((len(ksi[10:20])))\n",
    "\n",
    "for i in range(10,len(ksi)-1):\n",
    "    REk[i-10] = abs(ksi[i]-ksiN[i])/ksi[i]\n",
    "    \n",
    "MREk = np.mean(REk)\n",
    "MREk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "159cad2e-1d98-4620-a0b1-03b556cdd3b4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.864126130167909"
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Rsquared(ksiN[10:20],ksi[10:20])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "054a8fcb-e882-4d83-83a2-c07ab0efd145",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1d9e14a2b10>"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,4))\n",
    "\n",
    "plt.subplot(1,2,1)\n",
    "plt.plot(dmax[:20],Eabs[:20],color='k',label='Refined Base Plate Model (Malhotra & Veletsos, 1994)')\n",
    "plt.plot(dmaxN[:20],EabsN[:20],color='grey',label='Simplified uniaxial material')\n",
    "plt.xlim(0,1)\n",
    "plt.ylim(0,1500)\n",
    "plt.xlabel(r'Uplift, $w$ (m)',fontsize=12)\n",
    "plt.ylabel(r'Absorbed Energy (kJ)',fontsize=12)\n",
    "plt.legend()\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "plt.plot(dmax[10:20]/wy,ksi[10:20],'o',color='k',label='Refined Base Plate Model (Malhotra & Veletsos, 1994)')\n",
    "plt.plot(dmaxN[10:20]/wy,ksiN[10:20],'o',color='grey',label='Simplified uniaxial material')\n",
    "plt.xlim(0,50)\n",
    "plt.ylim(0,0.2)\n",
    "plt.xlabel(r'Uplift Ductility, $\\mu_{w}$',fontsize=12)\n",
    "plt.ylabel(r'Equivalent Viscous Damping Ratio, $\\xi_{eq}$',fontsize=12)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "16ef7c75-7034-45ab-a002-2b6169bb791b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "9c6f3117-4d40-43a9-b383-281611154d46",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "n = np.linspace(0,145,145, dtype='int')\n",
    "gamma = fillr*H/R\n",
    "vn = np.zeros(len(n))\n",
    "for i in range(len(n)):\n",
    "    vn[i] = np.pi*(2*n[i]+1)/2\n",
    "    \n",
    "I1 = np.zeros(len(n))\n",
    "I1p = np.zeros(len(n))\n",
    "\n",
    "for i in range(len(n)):\n",
    "    I1[i] = scp.special.i1(vn[i]/gamma)\n",
    "    I1p[i] = scp.special.i0(vn[i]/gamma)- scp.special.i1(vn[i]/gamma)/(vn[i]/gamma)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "0a9f2a36-d2d5-4e74-b1ca-ea509eb383ee",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "mi = np.sum(2*mtot*gamma*(I1/(I1p*vn**3)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "07e3d09a-14ce-4bb6-9903-e29ede87766d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5917228188566012"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mi/mtot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "3efc7029-16bb-4e1b-9771-27a104f8cc83",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "hi = H*np.sum((-1)**n*I1*(vn*(-1)**n-1)/(vn**4*I1p))/np.sum((I1/(I1p*vn**3)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "25ad76c9-630b-4d1d-a1a6-e62e0f3bb6bf",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.702689319167032"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "a3d5dd75-7b72-4f12-bd07-715b4030b4b0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "Ci = 6.2\n",
    "ro = 998\n",
    "tw = 17.7/1000\n",
    "Es1 = Es*1000\n",
    "Ti = Ci*H*(ro/Es1)**0.5/(tw/R)**0.5\n",
    "ki = 4*np.pi**2*mi/Ti**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "2e45154f-e4df-4acf-930d-cd559ee56f88",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "lam1 = 1.8412\n",
    "mc = mtot*2*np.tanh(lam1*gamma)/(lam1*gamma*(lam1**2-1))\n",
    "g = 9.805"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "93573e94-9f8e-4e4c-8f31-d945e6d0afb1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.39055060338333925"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mc/mtot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "04f8ac5b-d211-4ca9-a2ff-d92fdea792e8",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "hc = H*(1+(1-np.cosh(lam1*gamma))/(lam1*gamma*np.sinh(lam1*gamma)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "7dd64463-8374-4845-94c7-955885dc89da",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.324095026568012"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "b423bbaa-34a3-41e6-859e-e2c41b361993",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "Tc = 2*np.pi*(R/g)**0.5/(lam1*np.tanh(lam1*H/R))**0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "30b5435d-da2f-4918-8382-0134ce3d536c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.583430116180643"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Tc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "266cb6a2-8640-40d5-8137-27f94562bdd7",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def Base_Shear(L):\n",
    "    mm = 1-((L)/(2*R))\n",
    "    thm = np.arctan(mm/(1-mm))\n",
    "    km = (2/(thm)**2)*(1-np.cos(thm))\n",
    "    Wsm = Wtot*(1-mm**2)\n",
    "    Wfm = Wtot-Wsm\n",
    "    Mm=Wsm*km*R+Wfm*R*(1-mm)\n",
    "    Vm = Mm/hi\n",
    "    return Vm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "3e66127a-61ce-43ab-b015-7ab0b830ea9f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5187.479411885609"
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Vyt = Base_Shear(Ly)\n",
    "Vyt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "3d2a5b72-8f01-472c-944b-018a0258dd3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0018434821146207704"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wy*hi/(2*R)+Vyt/ki"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "63ea2ff4-e3d1-4427-9114-be7e647584e8",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "jmI = np.loadtxt('C:/Users/rober/Documents/ROSE/PostDoc/Tanks/DDBDTanks/Tank Archetypes/Tank A/FBD/ResultsJM/dispI.out')\n",
    "upliftI = np.loadtxt('C:/Users/rober/Documents/ROSE/PostDoc/Tanks/DDBDTanks/Tank Archetypes/Tank A/FBD/ResultsJM/UpliftI.out')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "id": "cc93b6fc-22d1-418d-960d-5636073fd3f7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "46.91170045299987\n"
     ]
    }
   ],
   "source": [
    "ApoI = np.trapz(jmI[:,0],jmI[:,1])\n",
    "dyI = 0.003\n",
    "VyI = 5500\n",
    "dmaxI = 0.1\n",
    "VmaxI = jmI[-1,0]\n",
    "\n",
    "AblI = dyI*VyI*0.5+(VmaxI+VyI)*0.5*(dmaxI-dyI)\n",
    "print(abs(AblI-ApoI))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "4281113e-0cea-4160-afeb-a2d966b67a31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 33301.8)"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(jmI[:,1],jmI[:,0])\n",
    "plt.plot((0,dyI),(0,VyI),color='k')\n",
    "plt.plot((dyI,dmaxI),(VyI,VmaxI),color='k')\n",
    "plt.plot((0,dmaxI),(0.1*VyI,0.1*VyI),color='k',ls='--')\n",
    "plt.xlabel(r'Displacement of impulsive mass, $\\Delta_{i}$ (m)')\n",
    "plt.ylabel(r'Force, $F$ (kN)')\n",
    "plt.xlim(0)\n",
    "plt.ylim(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "id": "ac759354-8b47-4699-a038-c894e3e33f51",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.05682192511170747"
      ]
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(Vyt-VyI)/VyI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "c54c0929-aefb-4cb2-b10e-cf4dd86e61f2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.053774203458775"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(upliftI[:,1],jmI[:,1])\n",
    "plt.plot(upliftI[:,1],upliftI[:,1]*(hi/(2*R))+jmI[:,0]/ki)\n",
    "plt.ylabel(r'Displacement of impulsive mass, $\\Delta_{i}$ (m)')\n",
    "plt.xlabel(r'Uplift, $w$ (m)')\n",
    "(wpl1*hi/(2*R)*1.2)/dyI"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
